An integrated approach to epitope analysis II: A system for proteomic-scale prediction of immunological characteristics

Background

Improving our understanding of the immune response is fundamental to developing strategies to combat a wide range of diseases. We describe an integrated epitope analysis system which is based on principal component analysis of sequences of amino acids, using a multilayer perceptron neural net to conduct QSAR regression predictions for peptide binding affinities to 35 MHC-I and 14 MHC-II alleles.

Results

The approach described allows rapid processing of single proteins, entire proteomes or subsets thereof, as well as multiple strains of the same organism. It enables consideration of the interface of diversity of both microorganisms and of host immunogenetics. Patterns of binding affinity are linked to topological features, such as extracellular or intramembrane location, and integrated into a graphical display which facilitates conceptual understanding of the interplay of B-cell and T-cell mediated immunity. Patterns which emerge from application of this approach include the correlations between peptides showing high affinity binding to MHC-I and to MHC-II, and also with predicted B-cell epitopes. These are characterized as coincident epitope groups (CEGs). Also evident are long range patterns across proteins which identify regions of high affinity binding for a permuted population of diverse and heterozygous HLA alleles, as well as subtle differences in reactions with MHCs of individual HLA alleles, which may be important in disease susceptibility, and in vaccine and clinical trial design. Comparisons are shown of predicted epitope mapping derived from application of the QSAR approach with experimentally derived epitope maps from a diverse multi-species dataset, from Staphylococcus aureus, and from vaccinia virus.

Conclusions

A desktop application with interactive graphic capability is shown to be a useful platform for development of prediction and visualization tools for epitope mapping at scales ranging from individual proteins to proteomes from multiple strains of an organism. The possible functional implications of the patterns of peptide epitopes observed are discussed, including their implications for B-cell and T-cell cooperation and cross presentation.     

An automated method for finding molecular complexes in large protein interaction networks

Background  

Recent advances in proteomics technologies such as two-hybrid, phage display and mass spectrometry have enabled us to create a detailed map of biomolecular interaction networks. Initial mapping efforts have already produced a wealth of data. As the size of the interaction set increases, databases and computational methods will be required to store, visualize and analyze the information in order to effectively aid in knowledge discovery.     

Chimeric foot-and-mouth disease virus serotype O displaying a serotype Asia1 antigenic epitope at the surface

Objective

To determine whether the G–H loop of foot-and-mouth disease virus (FMDV) serotype O can function as a target structure to harbour and display serotype Asia1 antigenic epitope at the surface.

Results

Using reverse genetics, FMDV serotype O IND R2/1975 displaying a FMDV serotype Asia1 B cell epitope at the capsid surface was constructed. The epitope-inserted recombinant chimeric virus was genetically stable up to ten serial passages in cell culture and exhibited growth properties similar to the parental serotype O virus. Furthermore, the surface-displayed Asia1 epitope able to react with serotype Asia1 specific antibodies in a competitive ELISA. Importantly, the recombinant chimeric virus showed neutralizing activity to both serotype O and Asia1 polyclonal antibodies.

Conclusion

The capsid protein of FMDV serotype O can effectively display potent epitope of other serotypes, making this an attractive approach for the design of new generation bi-valent FMD vaccines.

     

Affinity maturation generates greatly improved xyloglucan-specific carbohydrate binding modules

Background  

Molecular evolution of carbohydrate binding modules (CBM) is a new approach for the generation of glycan-specific molecular probes. To date, the possibility of performing affinity maturation on CBM has not been investigated. In this study we show that binding characteristics such as affinity can be improved for CBM generated from the CBM4-2 scaffold by using random mutagenesis in combination with phage display technology.     

Pichia surface display: display of proteins on the surface of glycoengineered Pichia pastoris strains

Expression of proteins on the surface of yeasts has a wide range of applications in biotechnology, such as directed evolution of proteins for increased affinity and thermal stability, screening of antibody libraries, epitope mapping, and use as whole-cell biocatalysts. However, hyperglycosylation can interfere with overall protein accessibility on the surface. Therefore, the less elaborate hyperglycosylation in wild type Pichia pastoris and the availability of glycoengineered strains make this yeast an excellent alternative for surface display of glycoproteins. Here, we report the implementation of the well-established a-agglutinin-based yeast surface display technology in P. pastoris. Four heterologous proteins were expressed on the surface of a wild type and a glycoengineered strain. Surface display levels were monitored by Western blot, immunofluorescence microscopy, and FACS analysis. The availability of glycoengineered strains makes P. pastoris an excellent alternative for surface display of glycoproteins and paves the way for new applications. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

A straightforward protocol for the preparation of high performance microarray displaying synthetic MUC1 glycopeptides

Background

Human serum MUC1 peptide fragments bearing aberrant O-glycans are secreted from columnar epithelial cell surfaces and known as clinically important serum biomarkers for the epithelial carcinoma when a specific monoclonal antibody can probe disease-relevant epitopes. Despite the growing importance of MUC1 glycopeptides as biomarkers, the precise epitopes of most anti-MUC1 monoclonal antibodies remains unclear.

Methods

A novel protocol for the fabrication of versatile microarray displaying peptide/glycopeptide library was investigated for the construction of highly sensitive and accurate epitope mapping assay of various anti-MUC1 antibodies.

Results

Selective imine-coupling between aminooxy-functionalized methacrylic copolymer with phosphorylcholine unit and synthetic MUC1 glycopeptides-capped by a ketone linker at N-terminus provided a facile and seamless protocol for the preparation of glycopeptides microarray platform. It was demonstrated that anti-KL-6 monoclonal antibody shows an extremely specific and strong binding affinity toward MUC1 fragments carrying sialyl T antigen (Neu5Acα2,3Galβ1,3GalNAcα1→) at Pro-Asp-Thr-Arg motif when compared with other seven anti-MUC1 monoclonal antibodies such as VU-3D1, VU-12E1, VU-11E2, Ma552, VU-3C6, SM3, and DF3. The present microarray also uncovered the occurrence of IgG autoantibodies in healthy human sera that bind specifically with sialyl T antigen attached at five potential O-glycosylation sites of MUC1 tandem repeats.

Conclusion

We established a straightforward strategy toward the standardized microarray platform allowing highly sensitive and accurate epitope mapping analysis by reducing the background noise due to nonspecific protein adsorption.

General significance

The present approach would greatly accelerate the discovery research of new class autoantibodies as well as the development of therapeutic mAbs reacting specifically with disease-relevant epitopes.     

Antibody-protein interactions: benchmark datasets and prediction tools evaluation

Background  

The ability to predict antibody binding sites (aka antigenic determinants or B-cell epitopes) for a given protein is a precursor to new vaccine design and diagnostics. Among the various methods of B-cell epitope identification X-ray crystallography is one of the most reliable methods. Using these experimental data computational methods exist for B-cell epitope prediction. As the number of structures of antibody-protein complexes grows, further interest in prediction methods using 3D structure is anticipated. This work aims to establish a benchmark for 3D structure-based epitope prediction methods.     

EPSVR and EPMeta: prediction of antigenic epitopes using support vector regression and multiple server results

Background  

Accurate prediction of antigenic epitopes is important for immunologic research and medical applications, but it is still an open problem in bioinformatics. The case for discontinuous epitopes is even worse - currently there are only a few discontinuous epitope prediction servers available, though discontinuous peptides constitute the majority of all B-cell antigenic epitopes. The small number of structures for antigen-antibody complexes limits the development of reliable discontinuous epitope prediction methods and an unbiased benchmark to evaluate developed methods.     

TCP: a tool for designing chimera proteins based on the tertiary structure information

Background  

Chimera proteins are widely used for the analysis of the protein-protein interaction region. One of the major issues is the epitope analysis of the monoclonal antibody. In the analysis, a continuous portion of an antigen is sequentially substituted into a different sequence. This method works well for an antibody recognizing a linear epitope, but not for that recognizing a discontinuous epitope. Although the designing the chimera proteins based on the tertiary structure information is required in such situations, there is no appropriate tool so far.     

Pep-3D-Search: a method for B-cell epitope prediction based on mimotope analysis

Background  

The prediction of conformational B-cell epitopes is one of the most important goals in immunoinformatics. The solution to this problem, even if approximate, would help in designing experiments to precisely map the residues of interaction between an antigen and an antibody. Consequently, this area of research has received considerable attention from immunologists, structural biologists and computational biologists. Phage-displayed random peptide libraries are powerful tools used to obtain mimotopes that are selected by binding to a given monoclonal antibody (mAb) in a similar way to the native epitope. These mimotopes can be considered as functional epitope mimics. Mimotope analysis based methods can predict not only linear but also conformational epitopes and this has been the focus of much research in recent years. Though some algorithms based on mimotope analysis have been proposed, the precise localization of the interaction site mimicked by the mimotopes is still a challenging task.     

A simple vector system to improve performance and utilisation of recombinant antibodies

Background  

Isolation of recombinant antibody fragments from antibody libraries is well established using technologies such as phage display. Phage display vectors are ideal for efficient display of antibody fragments on the surface of bacteriophage particles. However, they are often inefficient for expression of soluble antibody fragments, and sub-cloning of selected antibody populations into dedicated soluble antibody fragment expression vectors can enhance expression.     

Can ultrasound be used to stimulate nerve tissue?

Background  

The stimulation of nerve or cortical tissue by magnetic induction is a relatively new tool for the non-invasive study of the brain and nervous system. Transcranial magnetic stimulation (TMS), for example, has been used for the functional mapping of the motor cortex and may have potential for treating a variety of brain disorders.     

Integrating protein structures and precomputed genealogies in the Magnum database: Examples with cellular retinoid binding proteins

Background  

When accurate models for the divergent evolution of protein sequences are integrated with complementary biological information, such as folded protein structures, analyses of the combined data often lead to new hypotheses about molecular physiology. This represents an excellent example of how bioinformatics can be used to guide experimental research. However, progress in this direction has been slowed by the lack of a publicly available resource suitable for general use.     

Secondary structure spatial conformation footprint: a novel method for fast protein structure comparison and classification

Background  

Recently a new class of methods for fast protein structure comparison has emerged. We call the methods in this class projection methods as they rely on a mapping of protein structure into a high-dimensional vector space. Once the mapping is done, the structure comparison is reduced to distance computation between corresponding vectors. As structural similarity is approximated by distance between projections, the success of any projection method depends on how well its mapping function is able to capture the salient features of protein structure. There is no agreement on what constitutes a good projection technique and the three currently known projection methods utilize very different approaches to the mapping construction, both in terms of what structural elements are included and how this information is integrated to produce a vector representation.     

Efficient four fragment cloning for the construction of vectors for targeted gene replacement in filamentous fungi

Background  

The rapid increase in whole genome fungal sequence information allows large scale functional analyses of target genes. Efficient transformation methods to obtain site-directed gene replacement, targeted over-expression by promoter replacement, in-frame epitope tagging or fusion of coding sequences with fluorescent markers such as GFP are essential for this process. Construction of vectors for these experiments depends on the directional cloning of two homologous recombination sequences on each side of a selection marker gene.     

Computing power of quantitative trait locus association mapping for haploid loci

Background  

Statistical power calculations are a critical part of any study design for gene mapping. Most calculations assume that the locus of interest is biallelic. However, there are common situations in human genetics such as X-linked loci in males where the locus is haploid. The purpose of this work is to mathematically derive the biometric model for haploid loci, and to compute power for QTL mapping when the loci are haploid.     

Highly efficient selection of epitope specific antibody through competitive yeast display library sorting

Combinatory antibody library display technologies have been invented and successfully implemented for the selection and engineering of therapeutic antibodies. Precise targeting of important epitopes on the protein of interest is essential for such isolated antibodies to serve as effective modulators of molecular interactions. We developed a strategy to efficiently isolate antibodies against a specific epitope on a target protein from a yeast display antibody library using dengue virus envelope protein domain III as a model target. A domain III mutant protein with a key mutation inside a cross-reactive neutralizing epitope was designed, expressed, and used in the competitive panning of a yeast display naïve antibody library. All the yeast display antibodies that bound to the wild type domain III but not to the mutant were selectively sorted and characterized. Two unique clones were identified and showed cross-reactive binding to envelope protein domain IIIs from different serotypes. Epitope mapping of one of the antibodies confirmed that its epitope overlapped with the intended neutralizing epitope. This novel approach has implications for many areas of research where the isolation of epitope-specific antibodies is desired, such as selecting antibodies against conserved epitope(s) of viral envelope proteins from a library containing high titer, high affinity non-neutralizing antibodies, and targeting unique epitopes on cancer-related proteins.     

Prediction of antigenic epitopes on protein surfaces by consensus scoring

Background  

Prediction of antigenic epitopes on protein surfaces is important for vaccine design. Most existing epitope prediction methods focus on protein sequences to predict continuous epitopes linear in sequence. Only a few structure-based epitope prediction algorithms are available and they have not yet shown satisfying performance.